This story satisfactorily provides information about costs as well as quantifies benefits (although the story seems to "cherry-pick" the best outcomes), but overall feels like a promotional piece for lung cancer screening. While there are no obvious elements of disease mongering, there are elements of overstating the evidence of benefit for lung cancer screening. There is no mention of what type of study these findings are from (observational) or any cautionary statements about why there are limitations to these findings (because direct survival comparisons from an observational study are not possible and the study design could not account for all potential confounders). The concept that a survival advantage has not been demonstrated is mentioned only briefly at the end and is not given adequate coverage. Harms of screening are also not mentioned. The story presents a very rosy picture of screening and doesn't mention that screening can also lead to unnecessary treatment (like surgery) in some whose cancers may never have caused harm. While the story does disclose that its parent company makes CT scans, there is no independent comment on the study findings, or indeed, no balancing perspective included about why lung cancer screening may not be a good idea just yet.
The story states the cost of CT lung screening (about $200) and that it's not generally covered by insurance. However, the newscast also states this latest study will put pressure on payors to start paying for this screening test. While this may be true, this latest study still does not prove that lung cancer screening saves lives and widespread adoption of this practice is probably premature.
The story provides an estimated survival rate for those who get screened and get treatment if cancer is found. Because this is not a randomized clinical trial, an absolute risk reduction is not possible (because there is no control group to compare this to). However, the newscast chose to present the "best" outcomes in a select group of people by providing a rate of 92% who survived at 10 years if they got treatment. A better statistic would probably have been to report all people who survived at 10 years, whether or not they got treatment. Yet, the statistics used in the story are not incorrect.
The story does not mention any harms of treatment. Specifically, screening can lead to unnecessary treatment of cancers that may never have caused harm. Screening has downsides which were not mentioned at all.
The story does not adequately describe the strength of the evidence for the current findings. In other words, people don't know that this was an observational study with some limitations (the gold standard is a randomized controlled trial or RCT). Until an RCT is available, direct survival comparisons are difficult. This is a key limitation and is mentioned only briefly at the end of the story. The newscast presents a very rosy, unbalanced picture of the latest findings.
The story states that lung cancer is one of the deadliest forms of cancer, which is true. The newscast also describes that the earliest stage of lung cancers–stage I–is the most curable, which is accurate. No obvious embellishments about the disease state, but some overstatements about treatment ("treatment mongering"), although the latter is not officially evaluated here. For instance, the story leads with a statement that this could completely change how lung cancer is diagnosed, which is dramatic and probably premature given that experts still don't know whether it saves lives.
The story provides no independent comment on the results and notably does not present comments from experts who believe this type of screening is premature (because of the lack of randomized clinical trial or RCT data showing a survival benefit and because screening also has harms). Additionally, the lead author is allowed to promote her findings. Based on the observed study outcomes, the lead author describes who she believes should consider screening. This is probably premature given that a direct survival advantage has not been demonstrated (because this is not an RCT), although she does use language that leaves screening as a choice. The use of anecdotes, while engaging to viewers, is also prone to bias, particularly because the only anecdote is a positive one. There is no balancing perspective from someone in the study who experienced harms from screening.
The story states that most people are diagnosed at later stages (than stage I), but the point is that until now there hasn't been any screening strategy for lung cancer.
The article made a pretty good effort to talk about the availability of treatment, its cost, and the fact that insurance doesn't cover it because it is not yet widely accepted as standard of care.
The story states this could change how lung cancer is diagnosed, implying that this would be a new approach.
Systematic, Criteria-Driven
We’ve written about the hype of liquid biopsies for years (see link in comment below). And now this…. https://www.statnews.com/2022/01/12/medicare-shouldnt-cover-liquid-biopsies-early-cancer-detection/
Case counts still matter. “(There) are stories that may not be told adequately if only hospitalizations and deaths are emphasized.” @garyschwitzer interviewed by @dbauder of @AP. https://apnews.com/article/omicron-changing-news-outlets-covid-data-da9272f7c4c8a109c3bfb56bed9e9c76
My friend Gary @garyschwitzer wrote to his city council representative in a Minnesota town about a Viva Las Vegas event scheduled for January.
The response he got seems to perfectly capture where we are now.
https://www.healthnewsreview.org/2021/12/2021-ends-with-covid-craziness-in-sports-and-politics/
Comments (2)
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Melinda Wenner Moyer
November 30, 2011 at 2:21 pmHi Gary: a quick question. You mention that it’s impossible to mention absolute risk here because this is not a randomized controlled clinical trial and there is no control group. I understand that you need a comparison in order to calculate absolute risk differences, but is it possible to present absolute risks in certain types of observational studies? For instance, if there is a study comparing the effects of high versus low exposure to something, could you present an absolute risk analysis for the difference in risk observed in the high versus low exposure groups?
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